January 27, 2016
State of affairs has not changed: same process in 2005, 2008, and 2010
nrow(fleet_data) summary(fleet_data$NBR_POWER_UNIT) summary(fleet_data$DRIVER_TOTAL) summary(fleet_data$MCS150_MILEAGE)
> nrow(fleet_data)
[1] 1643373
> summary(fleet_data$NBR_POWER_UNIT)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0 1 1 5 2 599900
> summary(fleet_data$DRIVER_TOTAL)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.00e+00 1.00e+00 1.00e+00 5.25e+00 2.00e+00 3.00e+05
> summary(fleet_data$MCS150_MILEAGE)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000e+00 0.000e+00 1.200e+03 2.747e+05 4.000e+04 9.990e+09
> fleets_outlier[,c("LEGAL_NAME", "MCS150_DATE", "PHY_STATE",
"DRIVER_TOTAL", "NBR_POWER_UNIT", "MCS150_MILEAGE")]
LEGAL_NAME MCS150_DATE PHY_STATE DRIVER_TOTAL NBR_POWER_UNIT MCS150_MILEAGE
ALL RESTORED INC 17-DEC-15 DE 299998 1 0
507 TRUCKING INC. 18-DEC-15 CA 299971 599941 0
> fleet_data[fleet_data$NBR_POWER_UNIT == 599941,
c("DOT_NUMBER", "LEGAL_NAME", "EMAIL_ADDRESS", "PHY_ZIP")]
DOT_NUMBER LEGAL_NAME EMAIL_ADDRESS PHY_ZIP
1255558 2833526 507 TRUCKING INC. LAURASPERMITS@HOTMAIL.COM 92879
STATE_UNITS = state_choropleth( by_state_only, title = "Vehicle Population", legend = "Vehicles", num_colors = 1, zoom = NULL)
ZipChoropleth
does not produce country wide
by zipcode map
fleets_try = subset(
fleets, (NBR_POWER_UNIT < 2000) &
(DRIVER_TOTAL < 1000))
driver_unit_plot = ggplot(
fleets_try, aes(NBR_POWER_UNIT,
DRIVER_TOTAL )) +
geom_point(
aes(color=CARRIER_OPERATION)) +
xlab("Number of Units") +
ylab("Number of Drivers") +
ggtitle("Number of Drivers to Units relationship")
Analysis of inspection done: Issues with data coding
Relationship between fleets and inspections done
Takes over 37 billion gallons of diesel fuel to move all of that freight